Calculating individual carbon footprints

ABSTRACT

Behavior data associated with a user is obtained. The behavior data is generated when the user uses an Internet service and includes a user identification and identification information indicating the Internet service. At least one predefined carbon-saving quantity quantization algorithm is determined based on the identification information related to the Internet service. A carbon-saving quantity associated with the user is calculated based on the obtained behavior data and the determined at least one predefined carbon-saving quantity quantization algorithm. Based on the calculated carbon-saving quantity associated with the user and the user identification, user data is processed. The user data is related to the carbon-saving quantity associated with the user.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.15/684,603, filed on Aug. 23, 2017, which claims priority to ChineseApplication No. 201610717756.7, filed on Aug. 24, 2016, the entirecontents of which are hereby incorporated by reference.

TECHNICAL FIELD

The present disclosure relates to computer-implemented methods,software, and systems for calculating individual carbon footprints.

BACKGROUND

Various human activities generate carbon emissions (such as, greenhousegases) that can have negative effects on the Earth's environment. Forexample, driving a gasoline-powered car or operating a thermal powerstation generates carbon emissions. To control carbon emissions, it isimportant for an individual to be aware of their measured carbonfootprint based on daily behaviors.

SUMMARY

The present disclosure describes methods and systems, includingcomputer-implemented methods, computer program products, and computersystems for calculating individual carbon footprints, and particularlyfor calculating how many carbon footprints can be saved (that is, acarbon-saving quantity) from an individual engaging inenvironment-friendly behaviors.

In an implementation, behavior data associated with a user is obtained.The behavior data is generated when the user uses an Internet serviceand includes a user identification and identification informationindicating the Internet service. At least one predefined carbon-savingquantity quantization algorithm is determined based on theidentification information related to the Internet service. Acarbon-saving quantity associated with the user is calculated based onthe obtained behavior data and the determined at least one predefinedcarbon-saving quantity quantization algorithm. Based on the calculatedcarbon-saving quantity associated with the user and the useridentification, user data is processed. The user data is related to thecarbon-saving quantity associated with the user.

The previously described implementation is implementable using acomputer-implemented method; a non-transitory, computer-readable mediumstoring computer-readable instructions to perform thecomputer-implemented method; and a computer-implemented systemcomprising a computer memory interoperably coupled with a hardwareprocessor configured to perform the computer-implementedmethod/instructions stored on the non-transitory, computer-readablemedium.

The subject matter described in this specification can be implemented inparticular implementations, so as to realize one or more of thefollowing advantages. First, the described approach can be used to makeindividual people aware of their associated carbon footprints,carbon-saving quantities, or both from their daily behaviors. Forexample, fragmented behavior information associated with a person (auser) within a particular period of time (for example, a day, a month,or a year) can be aggregated. Based on the aggregated behavior data andin combination with a corresponding carbon-saving quantity quantizationalgorithm, a measurement of carbon footprints reduced by the user (thatis, a carbon-saving quantity) can be calculated and provided to theuser. Second, a service provider can provide a particular service, suchas a point accumulation, an account upgrade, or other service, for theuser based on the carbon-saving quantity associated with the user. Theparticular service can also provide incentives to the user to encouragereduction of carbon footprints by, for example, adopting moreenvironmentally-friendly behaviors. Other advantages will be apparent tothose of ordinary skill in the art.

The details of one or more implementations of the subject matter of thisspecification are set forth in the detailed description, the claims, andthe accompanying drawings. Other features, aspects, and advantages ofthe subject matter will become apparent from the detailed description,the claims, and the accompanying drawings.

DESCRIPTION OF DRAWINGS

FIG. 1 is a flowchart illustrating an example method for calculatingindividual carbon footprints, according to an implementation of thepresent disclosure.

FIGS. 2A-2E are schematic diagrams illustrating methods for generationof user behavior data in different scenarios, according to animplementation of the present disclosure.

FIG. 3 is a block diagram illustrating a computing-based architecturefor calculating individual carbon footprints, according to animplementation of the present disclosure.

FIGS. 4A-4C are illustrative screenshots related to point accumulation,according to an implementation of the present disclosure.

FIGS. 5A-5B are schematic diagrams of point acquisition between users,according to an implementation of the present disclosure.

FIG. 6 is a block diagram illustrating an example data processing systemfor calculating individual carbon footprints, according to animplementation of the present disclosure.

FIG. 7 is a block diagram illustrating an example computer system usedto provide computational functionalities associated with describedalgorithms, methods, functions, processes, flows, and procedures asdescribed in the instant disclosure, according to an implementation ofthe present disclosure.

Like reference numbers and designations in the various drawings indicatelike elements.

DETAILED DESCRIPTION

The following detailed description describes calculating individualcarbon footprints, particularly calculating a carbon-saving quantityassociated with a user based on collecting and aggregating fragmentedbehavior data associated with the user within a particular period oftime, and is presented to enable any person skilled in the art to makeand use the disclosed subject matter in the context of one or moreparticular implementations. Various modifications, alterations, andpermutations of the disclosed implementations can be made and will bereadily apparent to those of ordinary skill in the art, and the generalprinciples defined may be applied to other implementations andapplications, without departing from the scope of the disclosure. Insome instances, details unnecessary to obtain an understanding of thedescribed subject matter may be omitted so as to not obscure one or moredescribed implementations with unnecessary detail and as such detailsare within the skill of one of ordinary skill in the art. The presentdisclosure is not intended to be limited to the described or illustratedimplementations, but to be accorded the widest scope consistent with thedescribed principles and features.

Human activities can generate carbon emissions. To reduce carbonemissions, it is important to make people aware of their carbonfootprints from their daily behaviors. In addition, incentives can beprovided to encourage enterprises or individuals to take initiative tocontrol their carbon emissions by adopting environment-friendlybehaviors. For enterprises, since enterprise behaviors, in general, arerelatively closely related to the goals of the enterprise, eachenterprise can calculate and control its carbon footprints andcarbon-saving quantities. However, for individuals, as individualbehaviors are often unrelated to each other (that is, fragmented),carbon emissions can be generated from many different unrelated humanactivities. As a result, it is difficult for individual persons tocalculate their associated carbon footprints.

At a high-level, the described approach provides a mechanism toautomatically collect and aggregate behavior data associated with a userwithin a period of time. Based on aggregated behavior data and aparticular carbon-saving quantity quantization algorithm, carbonfootprints associated with the user, a carbon-saving quantity associatedwith the user, or a combination of carbon footprints and a carbon-savingquantity associated with the user can be calculated and provided to theuser. The carbon-saving quantity associated with the user can be furtherprocessed by a service provider to provide a particular service, such aspoint accumulation or account upgrade, for the user.

FIG. 1 is a flowchart illustrating an example method 100 for calculatingindividual carbon footprints, according to an implementation of thepresent disclosure. For clarity of presentation, the description thatfollows generally describes method 100 in the context of the otherfigures in this description. However, it will be understood that method100 may be performed, for example, by any suitable system, environment,software, and hardware, or a combination of systems, environments,software, and hardware, as appropriate. In some implementations, varioussteps of method 100 can be run in parallel, in combination, in loops, orin any order.

At 105, behavior data associated with a user is acquired. For example,the acquired behavior data can be generated when the user uses anInternet service. In some implementations, the behavior data can includea user identification (such as a user ID or a user account) andidentification information that indicates the Internet service used whenthe behavior data is generated. The Internet service can include, forexample, at least one of an Internet-based (or “online”) electronicpayment service, a reservation service, a ticketing service, a paymentservice, a health service, or other Internet service consistent withthis disclosure. In some implementations, the health service can be aservice associated with a mobile phone system or an application formonitoring user movement behavior. In some implementations, the healthservice can include, for example, at least one of a step-countingservice and a distance calculation service. In some implementations,different Internet services can have different identificationinformation, which can include, for example, at least one of a servicetype identification and a type identification bit in an order number. Asa result, a type of an Internet service corresponding to the behaviordata can be determined based on the identification information in thebehavior data. In some implementations, behavior data from differentInternet services can be differentiated based on the identificationinformation included in the behavior data from the different Internetservices.

In some implementations, the acquired behavior data can includefragmented behavior data. Each fragment of the behavior data can includea user identification (such as a user ID or a user account) andidentification information indicating the Internet service correspondingto the particular fragment of the behavior data. To aggregate thefragmented behavior data, all the fragments of the behavior data aretoned to include identification related to the same user in order tocorrelate the fragments of the behavior data. In some implementations, auser can use different Internet services through different applicationsor servers when generating behavior data. For example, the user can usean online payment service through a payment application on a mobilecomputing device and use an online meal-ordering service through ameal-ordering application. In some implementations, a user can usedifferent accounts when using the Internet services. To ensure that theacquired behavior data is associated with the same user, the differentaccounts (that is, user identifications) related to the same user may beacquired. For example, the user can first input information related totheir different accounts to be stored. Then, behavior data associatedwith an account can be acquired from a corresponding application orserver through, for example, an account name of the user. In someimplementations, data or combinations of data identifying the user canbe used to acquire the behavior data. Note that the previously describedmethod is not limited to acquisition of different accounts related to asame user, but also applicable to acquisition of different accountsrelated to different users.

In some implementations, after the behavior data is acquired, a field,representing a type of an Internet service, in the behavior data can bedetermined based on a predefined rule. Based on content in the field,the type of Internet service corresponding to the behavior data can bedetermined. In some implementations, types of Internet services providedby some applications or servers are relatively fixed. For example, aticketing website server only provides a ticketing service. If behaviordata is acquired from such applications or servers, types of Internetservices corresponding to the behavior data can be identified directlybased on, for example, at least one of names, domain names, UniversalResource Locators (URLs), and other information associated with theapplications or servers.

In some implementations, method 100 can be performed by an application.In some implementations, method 100 can be performed by a server. Whenperformed by an application, the application may be capable of providingvarious Internet services to the user. In that case and in someimplementations, the application can be configured to generate behaviordata for the user and to also calculate carbon footprints for the userdirectly based on the generated behavior data. In other words, byregistering an account in the application, behavior data generated bythe user through use of various Internet services in the application canbe associated with the user's registered account. As a result, theapplication only needs to acquire behavior data related to the accountto calculate, for example, carbon footprints for the user.

However, if the application cannot itself provide an Internet service tothe user, the application can initiate a request for acquiring behaviordata from a third-party application or a third-party server capable ofproviding an Internet service. Then, the application may receive thebehavior data from the third-party application, or synchronize data withthe third-party application to receive the behavior data generated bythe third-party application. In that case, the user may input, in theapplication, different third-party accounts associated with the user, aswell as third-party applications or third-party servers corresponding tothe different third-party accounts. The application can then associatethe third-party accounts with an account registered by the user in theapplication. For example, to acquire behavior data from a third-partyapplication, the application can determine, based on a third-partyaccount, a third-party application corresponding to the third-partyaccount, and send an acquisition request that carries the third-partyaccount to the third-party application. In response, the third-partyapplication can find behavior data related to the third-party accountand return the behavior data to the requesting application. As a result,the application can acquire the user behavior data.

In some implementations, when a third-party application is involved incalculating individual carbon footprints, the application that performsmethod 100 can register, in advance, with the third-party application.By registering with the third-party application, the application canreceive behavior data from the third-party application. In someimplementations, when a third-party server is involved in calculatingindividual carbon footprints, the application that performs method 100can acquire behavior data from the third-party server through a datatransfer protocol that both the application and the third-party serveragree upon.

In some implementations, behavior data is generated, by a third-partyapplication or a third-party server, in a common data format. Forexample, the behavior data can be generated in a two-dimensional tableformat, a HyperText Markup Language (HTML) format, or an ExtensibleMarkup Language (XML) format. After acquiring the behavior data, theapplication or server that performs method 100 can read, analyze, orread and analyze the behavior data based on the corresponding dataformat. In some implementations, for a particular data format, theapplication that performs method 100 and a third-party application canagree upon a data transmission format (for example, a JavaScript ObjectNotation (JSON) format). In addition, different methods for analyzingdifferent data formats can be added, in advance, to an ApplicationProgramming Interface (API) of the application. In some implementations,the acquired behavior data can be stored locally or remotely. From 105,method 100 proceeds to 110.

At 110, at least one preset carbon-saving quantity quantizationalgorithm is determined according to the identification information ofthe Internet service in the acquired behavior data. In someimplementations, relationships between Internet services andcarbon-saving quantity quantization algorithms are pre-established.Based on a particular Internet service and the pre-establishedrelationships, at least one carbon-saving quantity quantizationalgorithm can be determined. The at least one carbon-saving quantityquantization algorithm includes, for example, a quantization formula, aquantization model, or a combination of a quantization formula and aquantization model.

In some implementations, behavior data including differentidentification information from different Internet services can beassociated with different carbon-saving quantity quantizationalgorithms. For example, an electronic payment service can save paperproducts, and a walking trip can save carbon emissions because a vehiclewas not driven (such as a gasoline-powered car). In someimplementations, an Internet service can be associated with multiplecarbon-saving quantity quantization algorithms (that is, multiplecarbon-saving quantity quantization algorithms can be used with oneInternet service). For example, when a user uses an online ticketingservice, the user can buy a ticket without leaving, for example, theuser's home. As a result, carbon emissions caused by a trip to aticketing site by driving a vehicle can be saved. In addition, buyingtickets online can avoid printing paper products, such as tickets,receipts, and reservation lists, during online payment. As a result,carbon emissions caused by the used paper products can be saved. Tocalculate a carbon-saving quantity associated with the user by using theonline ticketing service, both a carbon-saving quantity quantizationalgorithm associated with trips using a vehicle and a carbon-savingquantity quantization algorithm associated with the use of paperproducts are used.

In some implementations, the carbon-saving quantity quantizationalgorithms can include a first preset algorithm and a second presetalgorithm. For example, the first preset algorithm can be acarbon-saving quantity quantization algorithm associated with the use ofpaper products (such as, a carbon-saving quantity quantization algorithmfor savings related to avoidance of printing paper bills). The secondpreset algorithm can be a carbon-saving quantity algorithm associatedwith use of a vehicle (such as, a carbon-saving quantity quantizationalgorithm for savings related to walking as opposed to driving).

For the first preset algorithm, a carbon-saving quantity can becalculated based on a carbon emission corresponding to a paper product.For example, the following formula can be used:

ER _(y)=Σ_(i)(F _(i) ×AD _(i,y))×EF _(y)×10⁻⁶(1)   (1),

where ER_(y) is a carbon-saving quantity (unit: tons of CO2) of a paperbill saved by each online payment in the y^(th) year. In other words,ER_(y) represents, in essence, a carbon footprint corresponding to apaper bill printed for each offline payment. Since printing of a paperbill can be avoided if the user uses online payment, the value of ER_(y)can be used as a carbon-saving quantity of a paper bill saved by eachonline payment. i is a merchant type of offline payment. F_(i) is aproportion (that is, percentage) of i-type merchants using a point ofservice (POS) machine for payment. AD_(i, y) is the number of times(unit: times) that the user makes payment offline at the i-typemerchants in the y^(th) year. EF_(y) is a baseline emission factor(unit: g CO2/time) of offline payment in the y^(th) year. In someimplementations, EF_(y) can be determined based on emission intensitiesof bill paper manufacturers in different regions. For example, Table 1shows emission intensities of bill paper manufacturers in severalprovinces in China.

TABLE 1 Other Yunnan Zhejiang Shanxi provinces Emission intensities(tons 1.9296 2.0072 1.8834 1.4622 of CO2/ton of paper)

In some implementations, since the value of a carbon-saving quantitycorresponding to saving of a paper bill in each online payment service(that is, ER) is too small, the carbon-saving quantity is calculated onan annual basis (that is, ER_(y) as in Equation (1)). In someimplementations, a threshold number can be predefined to avoidcalculating a carbon-saving quantity each time the online paymentservice is being used. For example, after using the online paymentservice by more than the threshold number, a total carbon-savingquantity for using the online payment service the threshold number oftimes can be calculated.

For the second preset algorithm, a carbon-saving quantity can becalculated based on a carbon emission corresponding to a trip by drivinga vehicle to a service location (for example, a bank, a shop, arestaurant). For example, the following formula can be used:

P=L×W;   (2),

where L is a geographical distance (unit: miles) between a user locationwhen using an online service and a nearest service location, W is a meanvalue of carbon footprints generated by driving a vehicle for a mile,and P is the carbon footprints generated by driving the vehicle for thedistance L. From 110, method 100 proceeds to 115.

At 115, a carbon-saving quantity associated with the user is calculatedaccording to the behavior data and the determined at least one presetcarbon-saving quantity quantization algorithm. For the first presetalgorithm, production of paper products can be reduced each time theuser uses an online Internet service. As a result, the carbon-savingquantity is related to the number of times that the user uses the onlineInternet service. In addition, since carbon emission standards aredifferent in different regions, the carbon-saving quantity is alsorelated to the user's geographical location. In some implementations,when the first predefined algorithm is used to calculate a usercarbon-saving quantity, at least a number of times that the user uses anInternet service and a user's geographical location when the user usesthe Internet service are first determined. Then, the carbon-savingquantity is calculated based on the determined number of times that theuser uses the Internet service, the determined geographical position ofthe user when the user uses the Internet service, and the firstpredefined algorithm.

For the second preset algorithm, the carbon-saving quantity associatedwith the user is related to, for example, a number of walking steps or awalking distance associated with the user. In some implementations, whenthe second predefined algorithm is used to calculate a usercarbon-saving quantity, at least a number of walking steps or a walkingdistance associated with the user is determined. Then, the carbon-savingquantity is calculated based on the determined number of walking stepsor walking distance, and the second predefined algorithm.

In some implementations, when the Internet services and thecarbon-saving quantity quantization algorithms are in a one-to-onerelationship, a single carbon-saving quantity quantization algorithm canbe used to calculate a user carbon-saving quantity by using acorresponding Internet service.

In some implementations, when the Internet services and thecarbon-saving quantity quantization algorithms are in a one-to-manyrelationship, multiple carbon-saving quantity quantization algorithms,corresponding to a particular Internet service, can be used to calculatea user carbon-saving quantity by using the particular Internet service.

In some implementations, the acquired behavior data may includeredundant or irrelevant data, such as data not required to calculateindividual carbon footprints. For example, acquired behavior data for auser using an online ticketing service can include data related to theamount of money the user paid. In some implementations, the acquiredbehavior data may not be used directly. For example, when acarbon-saving quantity is calculated according to behavior dataassociated with a user using an online ticketing service, thecalculation may require a number of times the user uses the onlineticketing service. In some implementations, the behavior data isprocessed to determine an exact number of times the user uses the onlineticketing service. In other implementations, an approximate number oftimes the user uses the online ticketing service can be used. As aresult, before calculating a carbon-saving quantity, data collatingoperations, such as statistical collection, screening, and removal, canbe performed on the acquired behavior data. In some implementations, anapplication or server that performs method 100 may perform the datacollating operations on the behavior data. In some implementations, anapplication or server that performs method 100 and a behavior dataprovider can agree upon behavior data required for calculation. As aresult, the behavior data provider can perform the data collatingoperations on behavior data associated with a user before providing theprocessed behavior data to the application or server.

In some implementations, a quantized value, calculated based on thebehavior data and the carbon-saving quantity quantization algorithm, canrepresent a carbon footprint reduced by a user (that is, a carbon-savingquantity associated with the user). In some implementations, acarbon-saving quantity can be calculated on a predefined cycle period.In some implementations, a carbon-saving quantity can be calculatedbased on the number of times that the user uses an Internet service.From 115, method 100 proceeds to 120.

At 120, specific user data is processed according to the calculatedcarbon-saving quantity and the user identification. The specific userdata is related to a carbon-saving quantity. In some implementations,after the carbon-saving quantity associated with the user is calculated,data processing operations, such as statistical collection and analysis,can be performed on the carbon-saving quantity within a period of time(for example, a day, a month, or a year). In some implementations, thecalculated carbon-saving quantity can be converted into points based on,for example, a predefined conversion rule. The newly converted pointscan be added to total points associated with the user to obtain anupdated total points value. As the value of the total points increase,the carbon-saving quantity associated with the user increases.Accordingly, a service provider can provide different services to theuser based on the value of the total points. For example, virtual goodscorresponding to the total points can be assigned to the user. In someimplementations, the virtual goods have different display statescorresponding to differing total point values.

In some implementations, user identification can include a user account.The specific user data can include data, such as carbon-saving points, acarbon-saving level, a carbon-saving badge, and carbon-saving relatedvirtual goods, in the user account. After 120, method 100 stops.

FIGS. 2A-2E are schematic diagrams of methods 200, 210, 220, 230, and240 for generation of user behavior data in different scenarios,according to an implementation of the present disclosure. Methods 200,210, 220, 230, and 240 are presented as detailed views of the operationsof method 100 described in FIG. 1 in different scenarios. For clarity ofpresentation, the description that follows generally describes methods200, 210, 220, 230, and 240 in the context of the other figures in thisdescription. However, it will be understood that methods 200, 210, 220,230, and 240 may be performed, for example, by any suitable system,environment, software, and hardware, or a combination of systems,environments, software, and hardware, as appropriate. In someimplementations, various steps of methods 200, 210, 220, 230, and 240can be run in parallel, in combination, in loops, or in any order.

Scenario 1: a user uses an online ticketing service.

In some implementations, the online ticketing service can include atleast one of online booking, purchasing, and refunding services fortrain tickets, plane tickets, ship tickets, movie tickets, admissiontickets, and other tickets consistent with this disclosure. Compared tothe traditional ticketing service (that is, a user goes to a physicalticketing site to obtain a ticket), the online ticketing service cansave the user a trip to the physical ticketing site. If the trip istaken to the physical ticketing site, for example, by driving a vehicle,data related to carbon emissions generated by the trip can be saved. Inaddition, by using the online ticketing service, paper products (forexample, printed paper statements or receipts) used during ticketpurchase or refund can be reduced or eliminated.

After the user uses the online ticketing service, a service providerthat provides the online ticketing service (for example, a ticketingwebsite) can generate online ticketing data based on the user's onlineticketing behavior. The online ticketing data can be used as behaviordata for the user in using the online ticketing service. A carbon-savingquantity associated with using the online ticketing service can becalculated based on the behavior data.

The calculation of a carbon-saving quantity can be performed by anapplication client having a carbon-saving quantity computing function(hereinafter referred to as a computing application), or a server havinga carbon-saving quantity computing function. As an example, FIGS. 2A-2Eare described with the computing application performing thecarbon-saving quantity calculation. In general, the online ticketingservice is provided by a ticketing website. The user can use the onlineticketing service through an application corresponding to the ticketingwebsite (hereinafter referred to as a ticketing application). Behaviordata generated while the user is using the online ticketing service canbe generated by a server of the ticketing website (hereinafter referredto as a ticketing server).

FIG. 2A shows an example method 200 of acquiring and calculating a usercarbon-saving quantity purchasing a ticket online. In general, when auser purchases a ticket online, the user sends a ticket purchase requestto a ticketing server through a corresponding ticketing application. Theticket purchase request can include user information (for example,user's ID card number, name, a ticketing account registered in theticketing application) and ticket purchase information (for example,type, time, place of a ticket to be purchased). After receiving theticket purchase request, the ticketing server can issue a ticketaccording to the online ticket purchase request, generate ticketing dataassociated with the user, and record the ticketing data as behaviordata.

At 201, the computing application sends an acquisition request,including user information to the ticketing server, to acquire ticketingdata associated with the user. In some implementations, the acquisitionrequest can include time information indicating ticketing dataassociated with the user within a predefined cycle period (for example,a day). In some implementations, the acquisition request can include anaccount registered by the user in the computing application (hereinafterreferred to as a computing account) and a ticketing account associatedwith the user to the ticketing server. The ticketing server, then, candynamically acquire, according to the ticketing account, ticketing datarelated to the ticketing account, and actively push, according to thecomputing account, the ticketing data related to the ticketing accountto the computing application. In some implementations, if the computingapplication itself has an online ticketing service, and the user usesthe online ticketing service provided by the computing application, thecomputing application can acquire ticketing data generated by thecomputing application. From 201, method 200 proceeds to 202.

At 202, the ticketing server receives the acquisition request,determines ticketing data corresponding to the user information includedin the acquisition request, and sends back the determined ticketing datato the computing application. The ticketing data includes at least auser ID, and identification information that reflects a type of theticketing service. In some implementations, if the acquisition requestincludes time information, the ticketing server can acquire, accordingto the time information, ticketing data associated with the usermatching the time information. In some implementations, the ticketingserver can perform data collating operations on the ticketing databefore sending the collated ticketing data to the computing application.For example, the ticketing data stored by the ticketing server mayinclude the amount of money for a purchased ticket, an origin of thepurchased ticket, and a destination of the purchased ticket. Theticketing server can remove the amount of money for the purchasedticket, the origin of the purchased ticket, and the destination of thepurchased ticket, from the ticketing data and send the processedticketing data to the computing application. From 202, method 200proceeds to 203.

At 203, after acquiring the ticketing data from the ticketing server,the computing application determines, according to the user ID includedin the ticketing data, that the ticketing data is associated with a useraccount. In addition, the computing application determines, according tothe identification information included in the ticketing data, at leastone carbon-saving quantity quantization algorithm for calculating acarbon-saving quantity of the ticketing data. The at least onecarbon-saving quantity quantization algorithm can be a carbon-savingquantity quantization algorithm specific to reduction of trips bydriving a vehicle, a carbon-saving quantity quantization algorithmspecific to savings related to the use of paper products, or acombination of a carbon-saving quantity quantization algorithm specificto reduction of trips by driving a vehicle and a carbon-saving quantityquantization algorithm specific to savings related to the use of paperproducts. From 203, method 200 proceeds to 204.

At 204, a carbon-saving quantity associated with the user using theonline ticketing service is calculated according to the determinedcarbon-saving quantity quantization algorithm and the acquired ticketingdata. In addition, specific user data can be processed according to thecalculated carbon-saving quantity associated with the user. In someimplementations, the ticketing application includes a locating functioncapable of determining the user's location information (for example, byusing global positioning system (GPS) or WIFI/cellular-triangulationinformation) when the user sends an online ticketing instruction. Thecomputing application can determine, according to a ticketing ordernumber in the acquired ticketing data, the number of times that the useruses the online ticketing service. The ticketing order number uniquelyidentifies, for example, one online ticketing service. In addition, thecomputing application can acquire, through the ticketing application,user location information when the user uses the online ticketingservice, and determine EF_(y) in Equation (1) according to a geographicregion corresponding to the user location information. Accordingly, acarbon-saving quantity specific to savings with respect to use of aprinted paper bill each time the user uses the online ticketing servicecan be calculated. If the user uses the online ticketing service n timesin a same geographic region, corresponding to the same EF_(y), acarbon-saving quantity associated with the user specific to savingsrelated to using printed paper bills can be calculated as n×ER_(y). Ifthe user uses the online ticketing service multiple times in differentgeographic regions, corresponding to different EF_(y), a carbon-savingquantity associated with the user specific to savings related to usingprinted paper bills is an accumulation of carbon-saving quantitiesassociated with the user in the different geographic regions.

In some implementations, the computing application can determine,according to the user location information when the user uses the onlineticketing service, a ticketing site location (for example, a railwaystation) closest to the user location. The computing application, then,calculates a distance L between the user location and the ticketing sitelocation, and uses Equation (2) to calculate a carbon-saving quantityspecific to avoidance of a trip by driving a vehicle for the distance L.In some implementations, the calculated carbon-saving quantityassociated with the user can include both a carbon-saving quantityspecific to avoidance of a trip by driving a vehicle, and acarbon-saving quantity specific to savings related to using printedpaper bills.

In some implementations, the calculated carbon-saving quantityassociated with the user using the online ticketing service can beconverted into points. After the user logs into the computingapplication, the points, indicating reduced carbon footprints by usingan online ticketing service, can be presented to the user. After 204,method 200 stops.

Scenario 2: a user uses an online payment service.

In some implementations, the online payment service can include at leastone of a face-to-face online payment service and an online transferservice. Compared to the traditional payment service, the online paymentservice can reduce consumption of paper products (for example, printedpaper bills), and thus can reduce carbon footprints.

After the user uses the online payment service, a service provider thatprovides the online payment service can generate online payment databased on the user's online payment behavior. The online payment data canbe used as behavior data for the user in using the online paymentservice. A carbon-saving quantity associated with using the onlinepayment service can be calculated based on the behavior data.

Similar to scenario 1, the calculation of a carbon-saving quantity canbe performed by a computing application or a server having acarbon-saving quantity computing function. In some implementations, aservice provider capable of providing the online payment serviceincludes a commodity website, a payment platform, and a bank. By takingthe payment platform as an example, the user can use the online paymentservice through an application corresponding to the payment platform(hereinafter referred to as a payment application). Behavior datagenerated while the user is using the online payment service can begenerated by a server of the payment platform (hereinafter referred toas a payment server).

FIG. 2B shows an example method 210 of acquiring and calculating a usercarbon-saving quantity making a payment online. In general, when a usermakes an online payment, the user sends a payment request to a paymentserver through a corresponding payment application. The payment requestcan include user information (for example, a payment account registeredby the user on the payment platform), target user information (forexample, a target account registered by the target user on the paymentplatform), and payment information (for example, the amount of payment).After receiving the payment request, the payment server can acquire,according to the received payment request, a fund matching the amount ofpayment from the payment account associated with the user, assign thefund to the target account of the target user, generate payment dataassociated with the user, and record the payment data as behavior data.

At 211, the computing application sends an acquisition request,including user information to the payment server, to acquire paymentdata associated with the user. In some implementations, when a user paysa target user online through the payment platform, the user and thetarget user each has a corresponding account registered on the paymentplatform. In some implementations, the acquisition request can include apayment account registered by the user on the payment platform toacquire payment data related to the payment account. In someimplementations, the acquisition request can include time informationindicating payment data associated with the user within a predefinedcycle period (for example, a day). In some implementations, thecomputing application can send, in advance, both a computing accountregistered by the user in the computing application and the paymentaccount associated with the user to the payment server. The paymentserver, then, can dynamically acquire, according to the payment account,payment data related to the payment account, and actively push,according to the computing account, the payment data related to thepayment account to the computing application. In some implementations,if the computing application itself has an online payment service andthe user uses the online payment service provided by the computingapplication, the computing application can acquire payment datagenerated by the computing application. From 211, method 210 proceeds to212.

At 212, the payment server receives the acquisition request, determinespayment data corresponding to the user information included in theacquisition request, and sends back the determined payment data to thecomputing application. The payment data includes at least a user ID, andidentification information that reflects a type of the payment service.In some implementations, if the acquisition request includes timeinformation, the payment server can acquire, according to the timeinformation, payment data associated with the user matching the timeinformation. In some implementations, the payment server can performdata collating operations on the payment data before sending thecollated payment data to the computing application. For example, thepayment data stored by the payment server may include the amount ofpayment, and the payment time. The payment server can remove the amountof payment and the payment time from the payment data and send theprocessed payment data to the computing application. From 212, method210 proceeds to 213.

At 213, after acquiring the payment data from the payment server, thecomputing application determines, according to the user ID included inthe payment data, that the payment data is associated with a useraccount. In addition, the computing application determines, according tothe identification information included in the payment data, acarbon-saving quantity quantization algorithm for calculating acarbon-saving quantity of the payment data. The carbon-saving quantityquantization algorithm can be a carbon-saving quantity quantizationalgorithm specific to savings related to the use of paper products. From213, method 210 proceeds to 214.

At 214, a carbon-saving quantity associated with the user using theonline payment service is calculated according to the determinedcarbon-saving quantity quantization algorithm and the acquired paymentdata. In addition, specific user data can be processed according to thecalculated carbon-saving quantity associated with the user. In someimplementations, the payment application includes a locating functioncapable of determining the user's location information (for example, byusing GPS or WIFI/cellular-triangulation information) when the usersends an online payment instruction. The computing application candetermine, according to a payment order number in the acquired paymentdata, the number of times that the user uses the online payment service.The payment order number uniquely identifies one online payment service.In addition, the computing application can acquire, through the paymentapplication, user location information when the user uses the onlinepayment service, and determine EF _(y) in Equation (1) according to ageographic region corresponding to the user location information.Accordingly, a carbon-saving quantity specific to savings with respectto use of a printed paper bill each time the user uses the onlinepayment service can be calculated. If the user uses the online paymentservice n times in a same geographic region, corresponding to the sameEF_(y), a carbon-saving quantity associated with the user specific tosavings related to using printed paper bills can be calculated asn×ER_(y). If the user uses the online payment service multiple times indifferent geographic regions, corresponding to different EF_(y), acarbon-saving quantity associated with the user specific to savingsrelated to using printed paper bills is an accumulation of carbon-savingquantities associated with the user in the different geographic regions.

In some implementations, the calculated carbon-saving quantityassociated with the user using the online payment service can beconverted into points. After the user logs into the computingapplication, the points, indicating reduced carbon footprints by usingan online payment service, can be presented to the user. After 214,method 211 stops.

Scenario 3: a user uses an online reservation service.

In some implementations, the online reservation service can include atleast one of online restaurant reservation, hotel reservation, venuebooking, and hospital registration services. Compared to the traditionalreservation service (that is, a user goes to a physical service site tomake a reservation), the online reservation service can save the user atrip to the physical service site. If the trip is taken to the physicalservice site, for example, by driving a vehicle, data related to carbonemissions generated by the trip can be saved.

After the user uses the online reservation service, a service providerthat provides the online reservation service (for example, a hospitalwebsite) can generate online reservation data based on the user's onlinereservation behavior. The online reservation data can be used asbehavior data for the user in using the online reservation service. Acarbon-saving quantity associated with using the online reservationservice can be calculated based on the behavior data.

Similar to scenario 1, the calculation of a carbon-saving quantity canbe performed by a computing application or a server having acarbon-saving quantity computing function. In some implementations, aservice provider capable of providing the online reservation serviceincludes a reservation platform, a hospital, a hotel, and a restaurant.By taking the reservation platform as an example, the user can use theonline reservation service through an application of the reservationplatform (hereinafter referred to as a reservation application).Behavior data generated while the user is using the online reservationservice can be generated by a server of the reservation platform(hereinafter referred to as a reservation server).

FIG. 2C shows an example method 220 of acquiring and calculating a usercarbon-saving quantity making a reservation online. In general, when auser makes an online reservation, the user sends a reservation requestto a reservation server through a corresponding reservation application.The reservation request can include user information (for example,medical insurance information of the user, user name, ID card number, areservation account registered by the user in the reservationapplication), registration type information (for example, a specialistnumber, an ordinary doctor number), and hospital information selected bythe user (for example, hospital level, hospital name). After receivingthe reservation request, the reservation server can register, accordingto the received reservation request, a corresponding hospital. After theregistration succeeds, the reservation server sends back an electronicregistration form to the reservation application, generates reservationdata associated with the user, and records the reservation data asbehavior data.

At 221, the computing application sends an acquisition request,including user information to the reservation server, to acquirereservation data associated with the user. In some implementations, theacquisition request can include a reservation account registered by theuser on the reservation platform to acquire reservation data related tothe reservation account. In some implementations, the acquisitionrequest can include medical insurance information of the user, username, ID card number, and a reservation account registered by the userin the reservation application. In some implementations, the acquisitionrequest can include time information indicating reservation dataassociated with the user within a predefined cycle period (for example,a day). In some implementations, the computing application can send botha computing account registered by the user in the computing applicationand the reservation account of the user to the reservation server. Thereservation server, then, can dynamically acquire, according to thereservation account, reservation data related to the reservationaccount, and actively push, according to the computing account, thereservation data related to the reservation account to the computingapplication. In some implementations, if the computing applicationitself has an online reservation service and the user uses the onlinereservation service provided by the computing application, the computingapplication can acquire reservation data generated by the computingapplication. From 221, method 220 proceeds to 222.

At 222, the reservation server receives the acquisition request,determines reservation data corresponding to the user informationincluded in the acquisition request, and sends back the determinedreservation data to the computing application. The reservation dataincludes at least a user ID, and identification information thatreflects a type of the reservation service. In some implementations, thereservation server can perform data collating operations on thereservation data before sending the collated reservation data to thecomputing application. For example, the reservation data stored by thereservation server may include a reservation type, and a date ofhospital visit. The reservation server can remove the reservation typeand the date of hospital visit from the reservation data, and send theprocessed reservation data to the computing application. From 222,method 220 proceeds to 223.

At 223, after acquiring the reservation data from the reservationserver, the computing application determines, according to the user IDincluded in the reservation data, that the reservation data isassociated with a user account. In addition, the computing applicationdetermines, according to the identification information included in thereservation data, a carbon-saving quantity quantization algorithm forcalculating a carbon-saving quantity of the reservation data. Thecarbon-saving quantity quantization algorithm can be a carbon-savingquantity quantization algorithm specific to reduction of trips bydriving a vehicle. From 223, method 220 proceeds to 224.

At 224, a carbon-saving quantity associated with the user using theonline reservation service is calculated according to the determinedcarbon-saving quantity quantization algorithm and the acquiredreservation data. In addition, specific user data can be processedaccording to the calculated carbon-saving quantity associated with theuser. In some implementations, the reservation application includes alocating function capable of determining the user's location information(for example, by using GPS or WIFI/cellular-triangulation information)when the user sends an online reservation instruction. The reservationdata acquired by the computing application can include the location ofthe user when the user uses the online reservation service. Based on ahospital address included in the reservation data, the computingapplication can determine the location of the hospital, calculate adistance L between the user location and the hospital location, and usesEquation (2) to calculate a carbon-saving quantity specific to avoidanceof a trip by driving a vehicle for the distance L.

In some implementations, the calculated carbon-saving quantityassociated with the user using the online reservation service can beconverted into points. After the user logs into the computingapplication, the points, indicating reduced carbon footprints by usingan online reservation service, can be presented to the user. After 224,method 220 stops.

Scenario 4: a user uses an online bill payment service.

In some implementations, the online bill payment service can include atleast one of paying water fees, electricity fees, natural gas fees, andtraffic fines online. Compared to the traditional bill payment service,the online bill payment service can save the user a trip to the physicalbill payment site. If the trip is taken to the physical bill paymentsite, for example, by driving a vehicle, data related to carbonemissions generated by the trip can be saved.

After the user uses the online bill payment service, a service providerthat provides the online bill payment service can generate online billpayment data based on the user's online bill payment behavior. Theonline bill payment data can be used as behavior data for the use inusing the online bill payment service. A carbon-saving quantityassociated with the user using the online bill payment service can becalculated based on the behavior data.

Similar to scenario 1, the calculation of a carbon-saving quantity canbe performed by a computing application or a server having acarbon-saving quantity computing function. In some implementations, aservice provider capable of providing the online bill payment serviceincludes an online bill payment platform, a bill payment website, and abank. By taking the bill payment platform as an example, the user canuse the online bill payment service through an application correspondingto the bill payment platform (hereinafter referred to as a bill paymentapplication). Behavior data generated while the user is using the onlinebill payment service can be generated by a server of the bill paymentplatform (hereinafter referred to as a bill payment server).

FIG. 2D shows an example method 230 of acquiring and calculating a usercarbon-saving quantity making a bill payment online. In general, when auser makes an online bill payment, the user sends a bill payment requestto a bill payment server through a corresponding bill paymentapplication. The bill payment request can include user information (forexample, driver's license number, ID card number, a penalty ticketnumber of the user, a bill payment account registered by the user on thebill payment platform). After receiving the bill payment request, thebill payment server can deduct, according to the received bill paymentrequest, a corresponding amount of fund from the account of the user,and pay the bill to the corresponding bill payment website. After thebill payment succeeds, the bill payment server sends back an electronicpayment voucher to the bill payment application, generates bill paymentdata associated with the user, and records the bill payment data asbehavior data.

At 231, the computing application sends an acquisition request,including user information to the bill payment server, to acquire billpayment data associated with the user. In some implementations, when auser makes an online bill payment, the user first registers acorresponding account on the bill payment platform. The account needs tohave sufficient amount of money to make the online bill paymentsuccessful. In some implementations, the acquisition request can includeat least one of a driver's license number, ID card number, a penaltyticket number of the user, and a bill payment account registered by theuser on the bill payment platform. In some implementations, theacquisition request can include time information indicating bill paymentdata associated with the user within a predefined cycle period (forexample, a day). In some implementations, the computing application cansend both a computing account registered by the user in the computingapplication and the bill payment account associated with the user to thebill payment server. The bill payment server, then, can dynamicallyacquire, according to the bill payment account, bill payment datarelated to the bill payment account, and actively push, according to thecomputing account, the bill payment data related to the bill paymentaccount to the computing application. In some implementations, if thecomputing application itself has an online bill payment service and theuser uses the online bill payment service provided by the computingapplication, the computing application can acquire bill payment datagenerated by the computing application. From 231, method 230 proceeds to232.

At 232, the bill payment server receives the acquisition request,determines bill payment data corresponding to the user informationincluded in the acquisition request, and sends back the determined billpayment data to the computing application. The bill payment dataincludes at least a user ID, and identification information thatreflects a type of the bill payment service. In some implementations,the bill payment server can perform data collating operations on thebill payment data before sending the collated bill payment data to thecomputing application. From 232, method 230 proceeds to 233.

At 233, after acquiring the bill payment data from the bill paymentserver, the computing application determines, according to the user IDincluded in the bill payment data, that the bill payment data isassociated with a user account. In addition, the computing applicationdetermines, according to the identification information included in thebill payment data, at least one carbon-saving quantity quantizationalgorithm for calculating a carbon-saving quantity of the bill paymentdata. The at least one carbon-saving quantity quantization algorithm canbe a carbon-saving quantity quantization algorithm specific to reductionof trips by driving a vehicle, a carbon-saving quantity quantizationalgorithm specific to savings related to the use of paper products, or acombination of a carbon-saving quantity quantization algorithm specificto reduction of trips by driving a vehicle and a carbon-saving quantityquantization algorithm specific to savings related to the use of paperproducts. From 233, method 230 proceeds to 234.

At 234, a carbon-saving quantity associated with the user using theonline bill payment service is calculated according to the determinedcarbon-saving quantity quantization algorithm and the acquired billpayment data. In addition, specific user data can be processed accordingto the calculated carbon-saving quantity associated with the user. Insome implementations, the bill payment application includes a locatingfunction capable of determining the user's location information (forexample, by using GPS or WIFI/cellular-triangulation information) whenthe user sends an online bill payment instruction. The computingapplication can determine, according to a bill payment order number inthe acquired bill payment data, the number of times that the user usesthe online bill payment service. The bill payment order number uniquelyidentifies one online bill payment service. In addition, the computingapplication can acquire, through the bill payment application, userlocation information when the user uses the online bill payment service,and determine EF_(y) in Equation (1) according to a geographic regioncorresponding to the user location information. Accordingly, acarbon-saving quantity specific to savings with respect to use of aprinted paper bill each time the user uses the online bill paymentservice can be calculated. If the user uses the online bill paymentservice n times in a same geographic region, corresponding to the sameEF_(y), a carbon-saving quantity associated with the user specific tosavings related to using printed paper bills can be calculated asn×ER_(y). If the user uses the online bill payment service multipletimes in different geographic regions, corresponding to differentEF_(y), a carbon-saving quantity associated with the user specific tosavings related to using printed paper bills is an accumulation ofcarbon-saving quantities associated with the user in the differentgeographic regions.

In some implementations, the computing application can determine,according to the user location information when the user uses the onlinebill payment service, a bill payment site location (for example, a bank)closest to the user location. The computing application, then,calculates a distance L between the user location and the bill paymentsite location, and uses Equation (2) to calculate a carbon-savingquantity specific to avoidance of a trip by driving a vehicle for thedistance L. In some implementations, the calculated carbon-savingquantity associated with the user can include both a carbon-savingquantity specific to avoidance of a trip by driving a vehicle, and acarbon-saving quantity specific to savings related to using printedpaper bills.

In some implementations, the calculated carbon-saving quantityassociated with the user using the online bill payment service can beconverted into points. After the user logs into the computingapplication, the points, indicating reduced carbon footprints by usingan online bill payment service, can be presented to the user. After 234,method 230 stops.

Scenario 5: a user goes out on foot, and walking data is monitored by ahealth service.

In some implementations, walking can reduce carbon footprints of a user.The user can walk to a physical service site. For example, the user canwalk to a hospital to register, walk to a ticketing site to purchase aticket, and walk to a bill payment site to pay related fees.

Walking data can be produced by a health service application (forexample, a walking application) having a walking data collectionfunction. The walking data can be used as behavior data for walking. Acarbon-saving quantity associated with the user can be calculated basedon the behavior data. In some implementations, the walking data caninclude at least one of the number of steps, location information duringwalking, and a walking distance. In some implementations, the walkingdata can include user information (for example, an account registered bythe user in the walking application).

Similar to scenario 1, the calculation of a carbon-saving quantity canbe performed by a computing application or a server having acarbon-saving quantity computing function. In some implementations, thewalking data can be obtained by a walking application through acorresponding collection algorithm, a model, or a sensing device (forexample, a smart bracelet, a smart watch).

FIG. 2E shows an example method 240 of acquiring and calculating a usercarbon-saving quantity by walking. At 241, the computing applicationsends an acquisition request, including user information to the walkingapplication, to acquire walking data associated with the user. In someimplementations, the acquisition request can include an accountregistered by the user on the walking application. In someimplementations, the walking application can actively push, according tothe registered account, walking data related to the user information tothe computing application. In some implementations, if the computingapplication itself has a walking data collection function, the computingapplication can acquire walking data generated by the computingapplication. From 241, method 240 proceeds to 242.

At 242, the walking application receives the acquisition request,determines walking data corresponding to the user information includedin the acquisition request, and sends back the determined walking datato the computing application. The walking data includes at least a userID, and identification information that reflects a type of a walkingbehavior. From 242, method 240 proceeds to 243.

At 243, after acquiring the walking data from the walking application,the computing application determines, according to the user ID includedin the walking data, that the walking data is associated with a useraccount. In addition, the computing application determines, according tothe identification information included in the walking data, acarbon-saving quantity quantization algorithm for calculating acarbon-saving quantity of the walking data. The carbon-saving quantityquantization algorithm can be a carbon-saving quantity quantizationalgorithm specific to reduction of trips by driving a vehicle. From 243,method 240 proceeds to 244.

At 244, a carbon-saving quantity associated with the user by walking iscalculated according to the determined carbon-saving quantityquantization algorithm and the acquired walking data. In addition,specific user data can be processed according to the calculatedcarbon-saving quantity associated with the user. In someimplementations, if the walking data includes location information ofthe user during walking, the computing application can determine, basedon the location information in the walking data, a walking distance ofthe user. The carbon-saving quantity associated with the user bywalking, then, can be determined based on the walking distance and thedetermined carbon-saving quantity quantization algorithm. After 244,method 240 stops.

FIG. 3 is a block diagram illustrating a computing-based architecture300 for calculating individual carbon footprints, according to animplementation of the present disclosure. As illustrated in FIG. 3, anapplication client 301 acquires fragmented user behavior data associatedwith a user 302, a third-party application 303, a third-party server304, or a combination of a third-party application 303 and a third-partyserver 304. The behavior data includes behavior data generated when theuser 302 uses different Internet services. After acquiring the behaviordata, the application client 301 sends the acquired behavior data to anapplication server 305. The application server 305 calculates acarbon-saving quantity associated with the user 302, and returns thecarbon-saving quantity to the application client 301 for presentation tothe user 302.

FIGS. 4A-4C are illustrative screenshots 400, 410, and 420 related topoint accumulation, according to an implementation of the presentdisclosure. For clarity of presentation, the description that followsgenerally describes screenshots 400, 410, and 420 in the context of theother figures in this description. In some implementations, pointaccumulation can be made in response to a confirming instruction sent bya user. For example, a control component configured to accumulate pointscan be provided to the user. The control component can be a suspensioncontrol component, an embedded control component, or a popup windowcontrol component, which can be implemented in hardware, software, orboth.

In FIG. 4A, a control component is embedded in an application interface401. The user can request point accumulation by clicking an “Accumulate”button 402. Based on this, accumulating the converted points and totalpoints of the user may include: after receiving a confirming instruction(that is, clicking the “Accumulate” button 402) sent by the user, pointsthat can be accumulated 403 are added to the total points 404 associatedwith the user.

Total points 404 can be calculated and displayed respectively accordingto different types of human behavior. As shown in FIG. 4B, theapplication interface includes different types of behavior items (forexample, payment 411, ticketing 412, walking 413, bill payment 414,reservation 415), and total points for each type of behavior item isdisplayed in each type of behavior item. In addition, total points forall types of behavior items can be displayed, for example, by clicking“Click to view total points” 416.

After clicking “Click to view total points” 416 in FIG. 4B, the totalpoints 421 for all types of behavior items is displayed as shown in FIG.4C.

In some implementations, different users can acquire non-accumulatedpoints from each other. For example, a user can send an acquisitioninstruction to acquire at least part of non-accumulated points of otherusers. As a result, the at least part of non-accumulated points of otherusers are deducted from accounts associated with the other users, andadded to the total points of the user. In some implementations, theother users are related to the user. For example, the other users arelisted in a user's contact list.

FIGS. 5A-5B are schematic diagrams 500 and 510 of point acquisitionbetween users, according to an implementation of the present disclosure.For clarity of presentation, the description that follows generallydescribes diagrams 500 and 510 in the context of the other figures inthis description. As shown in FIG. 5A, non-accumulated points aredisplayed for each contact in a user's contact list (Address list) 501.For example, contact Xiaoming 502 has 50 non-accumulated points, contactXiaohong 503 has 150 non-accumulated points 503, contact Xiaogang 504has 360 non-accumulated points, and contact Er'ya 505 has 0non-accumulated points. The user can click on any contact in the contactlist to acquire non-accumulated points of the clicked contact. As shownin FIG. 5B, after the user clicks on contact Xiaogang 504 in the contactlist 501, the user may be presented with a detailed view 511 of contactXiaogang 504. The detailed view 511 shows non-accumulated pointscorresponding to different types of behaviors of contact Xiaogang 504.For example, Xiaogang 504 has 100 non-accumulated points in Payment 512,50 non-accumulated points in Ticking 513, 100 non-accumulated points inWalking 514, 50 non-accumulated points in Bill payment 515, and 60non-accumulated points in Reservation 516. The user can click on aparticular behavior item (for example, Reservation) to acquirenon-accumulated points corresponding to the particular behavior item(for example, 60 non-accumulated points in Reservation).

In some implementations, virtual goods matching total points associatedwith a user can be assigned to the user. The virtual goods can include avirtual tree, a virtual badge, and a virtual medal. The virtual goodshave different display states according to differing total points. Forexample, according to pre-divided point intervals, a point intervalwithin which the total points fall can be determined, and a displaystate of the virtual goods associated with the user can be determinedbased on a predefined relationship between the point intervals anddisplay states of the virtual goods. The display states of the virtualgoods include, for example, a size, a shape, and a color of the virtualgoods. For example, a virtual medal can be a bronze medal, a silvermedal, or a gold medal.

FIG. 6 is a block diagram illustrating an example data processing system600 for calculating individual carbon footprints, according to animplementation. For clarity of presentation, the description thatfollows generally describes system 600 in the context of the otherfigures in this description. The system 600 can include an acquisitionunit 601, a determination unit 602, a calculation unit 603, a processingunit 604, a point acquisition unit 605, and an assignment unit 606,which can be implemented in hardware, software, or both.

The acquisition unit 601 can acquire behavior data associated with auser, as discussed in step 105 of FIG. 1. The determination unit 602 candetermine at least one preset carbon-saving quantity quantizationalgorithm based on identification information of an Internet service, asdiscussed in step 110 of FIG. 1 and steps 203, 213, 223, 233, and 243 ofFIGS. 2A-2E. The calculation unit 603 can calculate a carbon-savingquantity based on the acquired behavior data and the determined presetcarbon-saving quantity quantization algorithm, as discussed in step 115of FIG. 1 and steps 204, 214, 224, 234, and 244 of FIGS. 2A-2E. Theprocessing unit 604 can process specific user data based on thecalculated carbon-saving quantity and user identification, as discussedin step 120 of FIG. 1. In addition, the processing unit 604 can convertthe calculated carbon-saving quantity associated with the user intopoints based on a preset conversion rule, and accumulate the convertedpoints and total points of the user to obtain updated total points ofthe user. The point acquisition unit 605 can receive an acquisitioninstruction sent by a user for non-accumulated points of other users,acquire all or some points in the non-accumulated points of other users,and accumulate the acquired all or some points and total points of theuser to obtain updated total points of the user. The assignment unit 606can determine updated total points of the user, and assign virtual goodsmatching the updated total points to the user.

FIG. 7 is a block diagram of an example computer system 700 used toprovide computational functionalities associated with describedalgorithms, methods, functions, processes, flows, and procedures, asdescribed in the instant disclosure, according to an implementation. Theillustrated computer 702 is intended to encompass any computing devicesuch as a server, desktop computer, laptop/notebook computer, wirelessdata port, smart phone, personal data assistant (PDA), tablet computingdevice, one or more processors within these devices, or any othersuitable processing device, including physical or virtual instances (orboth) of the computing device. Additionally, the computer 702 maycomprise a computer that includes an input device, such as a keypad,keyboard, touch screen, or other device that can accept userinformation, and an output device that conveys information associatedwith the operation of the computer 702, including digital data, visual,or audio information (or a combination of information), or a graphicaluser interface (GUI).

The computer 702 can serve in a role as a client, network component, aserver, a database or other persistency, or any other component (or acombination of roles) of a computer system for performing the subjectmatter described in the instant disclosure. The illustrated computer 702is communicably coupled with a network 730. In some implementations, oneor more components of the computer 702 may be configured to operatewithin environments, including cloud-computing-based, local, global, orother environment (or a combination of environments).

At a high level, the computer 702 is an electronic computing deviceoperable to receive, transmit, process, store, or manage data andinformation associated with the described subject matter. According tosome implementations, the computer 702 may also include or becommunicably coupled with an application server, e-mail server, webserver, caching server, streaming data server, or other server (or acombination of servers).

The computer 702 can receive requests over network 730 from a clientapplication (for example, executing on another computer 702) and respondto the received requests by processing the received requests using anappropriate software application(s). In addition, requests may also besent to the computer 702 from internal users (for example, from acommand console or by other appropriate access method), external orthird-parties, other automated applications, as well as any otherappropriate entities, individuals, systems, or computers.

Each of the components of the computer 702 can communicate using asystem bus 703. In some implementations, any or all of the components ofthe computer 702, hardware or software (or a combination of bothhardware and software), may interface with each other or the interface704 (or a combination of both), over the system bus 703 using anapplication programming interface (API) 712 or a service layer 713 (or acombination of the API 712 and service layer 713). The API 712 mayinclude specifications for routines, data structures, and objectclasses. The API 712 may be either computer-language independent ordependent and refer to a complete interface, a single function, or evena set of APIs. The service layer 713 provides software services to thecomputer 702 or other components (whether or not illustrated) that arecommunicably coupled to the computer 702. The functionality of thecomputer 702 may be accessible for all service consumers using thisservice layer. Software services, such as those provided by the servicelayer 713, provide reusable, defined functionalities through a definedinterface. For example, the interface may be software written in JAVA,C++, or other suitable language providing data in extensible markuplanguage (XML) format or other suitable format. While illustrated as anintegrated component of the computer 702, alternative implementationsmay illustrate the API 712 or the service layer 713 as stand-alonecomponents in relation to other components of the computer 702 or othercomponents (whether or not illustrated) that are communicably coupled tothe computer 702. Moreover, any or all parts of the API 712 or theservice layer 713 may be implemented as child or sub-modules of anothersoftware module, enterprise application, or hardware module withoutdeparting from the scope of this disclosure.

The computer 702 includes an interface 704. Although illustrated as asingle interface 704 in FIG. 7, two or more interfaces 704 may be usedaccording to particular needs, desires, or particular implementations ofthe computer 702. The interface 704 is used by the computer 702 forcommunicating with other systems that are connected to the network 730(whether illustrated or not) in a distributed environment. Generally,the interface 704 comprises logic encoded in software or hardware (or acombination of software and hardware) and is operable to communicatewith the network 730. More specifically, the interface 704 may comprisesoftware supporting one or more communication protocols associated withcommunications such that the network 730 or interface's hardware isoperable to communicate physical signals within and outside of theillustrated computer 702.

The computer 702 includes a processor 705. Although illustrated as asingle processor 705 in FIG. 7, two or more processors may be usedaccording to particular needs, desires, or particular implementations ofthe computer 702. Generally, the processor 705 executes instructions andmanipulates data to perform the operations of the computer 702 and anyalgorithms, methods, functions, processes, flows, and procedures asdescribed in the instant disclosure.

The computer 702 also includes a database 706 that can hold data for thecomputer 702 or other components (or a combination of both) that can beconnected to the network 730 (whether illustrated or not). For example,database 706 can be an in-memory, conventional, or other type ofdatabase storing data consistent with this disclosure. In someimplementations, database 706 can be a combination of two or moredifferent database types (for example, a hybrid in-memory andconventional database) according to particular needs, desires, orparticular implementations of the computer 702 and the describedfunctionality. Although illustrated as a single database 706 in FIG. 7,two or more databases (of the same or combination of types) can be usedaccording to particular needs, desires, or particular implementations ofthe computer 702 and the described functionality. While database 706 isillustrated as an integral component of the computer 702, in alternativeimplementations, database 706 can be external to the computer 702.

The computer 702 also includes a memory 707 that can hold data for thecomputer 702 or other components (or a combination of both) that can beconnected to the network 730 (whether illustrated or not). Memory 707can store any data consistent with this disclosure. In someimplementations, memory 707 can be a combination of two or moredifferent types of memory (for example, a combination of semiconductorand magnetic storage) according to particular needs, desires, orparticular implementations of the computer 702 and the describedfunctionality. Although illustrated as a single memory 707 in FIG. 7,two or more memories 707 (of the same or combination of types) can beused according to particular needs, desires, or particularimplementations of the computer 702 and the described functionality.While memory 707 is illustrated as an integral component of the computer702, in alternative implementations, memory 707 can be external to thecomputer 702.

The application 708 is an algorithmic software engine providingfunctionality according to particular needs, desires, or particularimplementations of the computer 702, particularly with respect tofunctionality described in this disclosure. For example, application 708can serve as one or more components, modules, or applications. Further,although illustrated as a single application 708, the application 708may be implemented as multiple applications 708 on the computer 702. Inaddition, although illustrated as integral to the computer 702, inalternative implementations, the application 708 can be external to thecomputer 702.

The computer 702 can also include a power supply 714. The power supply714 can include a rechargeable or non-rechargeable battery that can beconfigured to be either user- or non-user-replaceable. In someimplementations, the power supply 714 can include power-conversion ormanagement circuits (including recharging, standby, or other powermanagement functionality). In some implementations, the power-supply 714can include a power plug to allow the computer 702 to be plugged into awall socket or other power source to, for example, power the computer702 or recharge a rechargeable battery.

There may be any number of computers 702 associated with, or externalto, a computer system containing computer 702, each computer 702communicating over network 730. Further, the term “client,” “user,” andother appropriate terminology may be used interchangeably, asappropriate, without departing from the scope of this disclosure.Moreover, this disclosure contemplates that many users may use onecomputer 702, or that one user may use multiple computers 702.

Described implementations of the subject matter can include one or morefeatures, alone or in combination.

For example, in a first implementation, a computer-implemented method,comprising: obtaining behavior data associated with a user, wherein thebehavior data is generated when the user uses an Internet service, andthe behavior data comprises a user identification and identificationinformation indicating the Internet service; determining at least onepredefined carbon-saving quantity quantization algorithm based on theidentification information of the Internet service; calculating acarbon-saving quantity associated with the user based on the obtainedbehavior data and the determined at least one predefined carbon-savingquantity quantization algorithm; and based on the calculatedcarbon-saving quantity associated with the user and the useridentification, processing user data, wherein the user data is relatedto the carbon-saving quantity associated with the user.

The foregoing and other described implementations can each, optionally,include one or more of the following features:

A first feature, combinable with any of the following features, whereinthe at least one predefined carbon-saving quantity quantizationalgorithm comprises: a first predefined algorithm, wherein the firstpredefined algorithm is a carbon-saving quantity quantization algorithmfor targeting savings of paper products; and a second predefinedalgorithm, wherein the second predefined algorithm quantizes acarbon-saving quantity of reduction of trips by taking vehicles.

A second feature, combinable with any of the previous or followingfeatures, wherein, when the first predefined algorithm is used tocalculate the carbon-saving quantity, calculating a carbon-savingquantity associated with the user comprises: based on the behavior data,determining at least a number of times that the user uses the Internetservice and a geographical location of the user when the user uses theInternet service; and calculating the carbon-saving quantity associatedwith the user based on the determined number of times that the user usesthe Internet service, the determined geographical position of the userwhen the user uses the Internet service, and the first predefinedalgorithm.

A third feature, combinable with any of the previous or followingfeatures, wherein, when the second predefined algorithm is used tocalculate the carbon-saving quantity, calculating a carbon-savingquantity associated with the user comprises: based on the behavior data,determining at least a number of walking steps or a walking distance ofthe user; and calculating the carbon-saving quantity associated with theuser based on the determined number of walking steps or walking distanceof the user and the second predefined algorithm.

A fourth feature, combinable with any of the previous or followingfeatures, wherein determining at least one predefined carbon-savingquantity quantization algorithm based on the identification informationof the Internet service comprises determining at least one predefinedcarbon-saving quantity quantization algorithm based on theidentification information of the Internet service and a plurality ofpre-stored corresponding relationships between a plurality of Internetservices and a plurality of carbon-saving quantity quantizationalgorithms.

A fifth feature, combinable with any of the previous or followingfeatures, wherein the Internet service comprises at least one of anelectronic payment service, an online reservation service, an onlineticketing service, an online bill payment service, and a health service.

A sixth feature, combinable with any of the previous or followingfeatures, wherein processing user data comprises: obtaining a pluralityof carbon-saving quantities associated with the user corresponding to aplurality of Internet services within a predefined period; accumulatingthe obtained plurality of carbon-saving quantities; and processing theuser data based on the accumulated carbon-saving quantity associatedwith the user.

A seventh feature, combinable with any of the previous or followingfeatures, wherein processing the user data based on the accumulatedcarbon-saving quantity associated with the user comprises: adding theaccumulated carbon-saving quantity associated with the user and a totalcarbon-saving quantity associated with the user together to obtain anupdated total carbon-saving quantity associated with the user; andprocessing the user data based on the updated total carbon-savingquantity associated with the user.

An eighth feature, combinable with any of the previous or followingfeatures, wherein adding the accumulated carbon-saving quantityassociated with the user and a total carbon-saving quantity associatedwith the user together to obtain an updated total carbon-saving quantityassociated with the user comprises: converting the accumulatedcarbon-saving quantity associated with the user into points based on apredefined conversion rule; and adding the converted points and totalpoints of the user together to obtain updated total points of the user.

A ninth feature, combinable with any of the previous or followingfeatures, wherein a control component configured to accumulate points isprovided to the user, and adding the converted points and total pointsof the user together to obtain updated total points of the usercomprises: receiving an instruction sent by the user through the controlcomponent confirming points accumulation; and adding the convertedpoints and the total points of the user together.

A tenth feature, combinable with any of the previous or followingfeatures, further comprising: receiving an instruction sent by the userto obtain non-accumulated points of other users; obtaining at least partof the non-accumulated points of other users in response to receivingthe instruction sent by the user to obtain non-accumulated points ofother users; and adding the obtained at least part of thenon-accumulated points of other users and the updated total points ofthe user together to obtain second updated total points of the user.

An eleventh feature, combinable with any of the previous or followingfeatures, further comprising determining the updated total points of theuser; and based on the updated total points of the user, assigning, tothe user, a virtual goods corresponding to the updated total points ofthe user.

A twelfth feature, combinable with any of the previous or followingfeatures, wherein the virtual goods has different display statescorresponding to different total points.

In a second implementation, a non-transitory, computer-readable mediumstoring one or more instructions executable by a computer system toperform operations comprising: obtaining behavior data associated with auser, wherein the behavior data is generated when the user uses anInternet service, and the behavior data comprises a user identificationand identification information indicating the Internet service;determining at least one predefined carbon-saving quantity quantizationalgorithm based on the identification information of the Internetservice; calculating a carbon-saving quantity associated with the userbased on the obtained behavior data and the determined at least onepredefined carbon-saving quantity quantization algorithm; and based onthe calculated carbon-saving quantity associated with the user and theuser identification, processing user data, wherein the user data isrelated to the carbon-saving quantity associated with the user.

The foregoing and other described implementations can each, optionally,include one or more of the following features:

A first feature, combinable with any of the following features, whereinthe at least one predefined carbon-saving quantity quantizationalgorithm comprises: a first predefined algorithm, wherein the firstpredefined algorithm is a carbon-saving quantity quantization algorithmfor targeting savings of paper products; and a second predefinedalgorithm, wherein the second predefined algorithm quantizes acarbon-saving quantity of reduction of trips by taking vehicles.

A second feature, combinable with any of the previous or followingfeatures, wherein, when the first predefined algorithm is used tocalculate the carbon-saving quantity, calculating a carbon-savingquantity associated with the user comprises: based on the behavior data,determining at least a number of times that the user uses the Internetservice and a geographical location of the user when the user uses theInternet service; and calculating the carbon-saving quantity associatedwith the user based on the determined number of times that the user usesthe Internet service, the determined geographical position of the userwhen the user uses the Internet service, and the first predefinedalgorithm.

A third feature, combinable with any of the previous or followingfeatures, wherein, when the second predefined algorithm is used tocalculate the carbon-saving quantity, calculating a carbon-savingquantity associated with the user comprises: based on the behavior data,determining at least a number of walking steps or a walking distance ofthe user; and calculating the carbon-saving quantity associated with theuser based on the determined number of walking steps or walking distanceof the user and the second predefined algorithm.

A fourth feature, combinable with any of the previous or followingfeatures, wherein determining at least one predefined carbon-savingquantity quantization algorithm based on the identification informationof the Internet service comprises determining at least one predefinedcarbon-saving quantity quantization algorithm based on theidentification information of the Internet service and a plurality ofpre-stored corresponding relationships between a plurality of Internetservices and a plurality of carbon-saving quantity quantizationalgorithms.

A fifth feature, combinable with any of the previous or followingfeatures, wherein the Internet service comprises at least one of anelectronic payment service, an online reservation service, an onlineticketing service, an online bill payment service, and a health service.

A sixth feature, combinable with any of the previous or followingfeatures, wherein processing user data comprises: obtaining a pluralityof carbon-saving quantities associated with the user corresponding to aplurality of Internet services within a predefined period; accumulatingthe obtained plurality of carbon-saving quantities; and processing theuser data based on the accumulated carbon-saving quantity associatedwith the user.

A seventh feature, combinable with any of the previous or followingfeatures, wherein processing the user data based on the accumulatedcarbon-saving quantity associated with the user comprises: adding theaccumulated carbon-saving quantity associated with the user and a totalcarbon-saving quantity associated with the user together to obtain anupdated total carbon-saving quantity associated with the user; andprocessing the user data based on the updated total carbon-savingquantity associated with the user.

An eighth feature, combinable with any of the previous or followingfeatures, wherein adding the accumulated carbon-saving quantityassociated with the user and a total carbon-saving quantity associatedwith the user together to obtain an updated total carbon-saving quantityassociated with the user comprises: converting the accumulatedcarbon-saving quantity associated with the user into points based on apredefined conversion rule; and adding the converted points and totalpoints of the user together to obtain updated total points of the user.

A ninth feature, combinable with any of the previous or followingfeatures, wherein a control component configured to accumulate points isprovided to the user, and adding the converted points and total pointsof the user together to obtain updated total points of the usercomprises: receiving an instruction sent by the user through the controlcomponent confirming points accumulation; and adding the convertedpoints and the total points of the user together.

A tenth feature, combinable with any of the previous or followingfeatures, further comprising: receiving an instruction sent by the userto obtain non-accumulated points of other users; obtaining at least partof the non-accumulated points of other users in response to receivingthe instruction sent by the user to obtain non-accumulated points ofother users; and adding the obtained at least part of thenon-accumulated points of other users and the updated total points ofthe user together to obtain second updated total points of the user.

An eleventh feature, combinable with any of the previous or followingfeatures, further comprising: determining the updated total points ofthe user; and based on the updated total points of the user, assigning,to the user, a virtual goods corresponding to the updated total pointsof the user.

A twelfth feature, combinable with any of the previous or followingfeatures, wherein the virtual goods has different display statescorresponding to different total points.

In a third implementation, a computer-implemented system, comprising:one or more computers; and one or more computer memory devicesinteroperably coupled with the one or more computers and havingtangible, non-transitory, machine-readable media storing instructions,that when executed by the one or more computers, perform operationscomprising: obtaining behavior data associated with a user, wherein thebehavior data is generated when the user uses an Internet service, andthe behavior data comprises a user identification and identificationinformation indicating the Internet service; determining at least onepredefined carbon-saving quantity quantization algorithm based on theidentification information of the Internet service; calculating acarbon-saving quantity associated with the user based on the obtainedbehavior data and the determined at least one predefined carbon-savingquantity quantization algorithm; and based on the calculatedcarbon-saving quantity associated with the user and the useridentification, processing user data, wherein the user data is relatedto the carbon-saving quantity associated with the user.

The foregoing and other described implementations can each, optionally,include one or more of the following features:

A first feature, combinable with any of the following features, whereinthe at least one predefined carbon-saving quantity quantizationalgorithm comprises: a first predefined algorithm, wherein the firstpredefined algorithm is a carbon-saving quantity quantization algorithmfor targeting savings of paper products; and a second predefinedalgorithm, wherein the second predefined algorithm quantizes acarbon-saving quantity of reduction of trips by taking vehicles.

A second feature, combinable with any of the previous or followingfeatures, wherein, when the first predefined algorithm is used tocalculate the carbon-saving quantity, calculating a carbon-savingquantity associated with the user comprises: based on the behavior data,determining at least a number of times that the user uses the Internetservice and a geographical location of the user when the user uses theInternet service; and calculating the carbon-saving quantity associatedwith the user based on the determined number of times that the user usesthe Internet service, the determined geographical position of the userwhen the user uses the Internet service, and the first predefinedalgorithm.

A third feature, combinable with any of the previous or followingfeatures, wherein, when the second predefined algorithm is used tocalculate the carbon-saving quantity, calculating a carbon-savingquantity associated with the user comprises: based on the behavior data,determining at least a number of walking steps or a walking distance ofthe user; and calculating the carbon-saving quantity associated with theuser based on the determined number of walking steps or walking distanceof the user and the second predefined algorithm.

A fourth feature, combinable with any of the previous or followingfeatures, wherein determining at least one predefined carbon-savingquantity quantization algorithm based on the identification informationof the Internet service comprises determining at least one predefinedcarbon-saving quantity quantization algorithm based on theidentification information of the Internet service and a plurality ofpre-stored corresponding relationships between a plurality of Internetservices and a plurality of carbon-saving quantity quantizationalgorithms.

A fifth feature, combinable with any of the previous or followingfeatures, wherein the Internet service comprises at least one of anelectronic payment service, an online reservation service, an onlineticketing service, an online bill payment service, and a health service.

A sixth feature, combinable with any of the previous or followingfeatures, wherein processing user data comprises: obtaining a pluralityof carbon-saving quantities associated with the user corresponding to aplurality of Internet services within a predefined period; accumulatingthe obtained plurality of carbon-saving quantities; and processing theuser data based on the accumulated carbon-saving quantity associatedwith the user.

A seventh feature, combinable with any of the previous or followingfeatures, wherein processing the user data based on the accumulatedcarbon-saving quantity associated with the user comprises: adding theaccumulated carbon-saving quantity associated with the user and a totalcarbon-saving quantity associated with the user together to obtain anupdated total carbon-saving quantity associated with the user; andprocessing the user data based on the updated total carbon-savingquantity associated with the user.

An eighth feature, combinable with any of the previous or followingfeatures, wherein adding the accumulated carbon-saving quantityassociated with the user and a total carbon-saving quantity associatedwith the user together to obtain an updated total carbon-saving quantityassociated with the user comprises: converting the accumulatedcarbon-saving quantity associated with the user into points based on apredefined conversion rule; and adding the converted points and totalpoints of the user together to obtain updated total points of the user.

A ninth feature, combinable with any of the previous or followingfeatures, wherein a control component configured to accumulate points isprovided to the user, and adding the converted points and total pointsof the user together to obtain updated total points of the usercomprises: receiving an instruction sent by the user through the controlcomponent confirming points accumulation; and adding the convertedpoints and the total points of the user together.

A tenth feature, combinable with any of the previous or followingfeatures, further comprising: receiving an instruction sent by the userto obtain non-accumulated points of other users; obtaining at least partof the non-accumulated points of other users in response to receivingthe instruction sent by the user to obtain non-accumulated points ofother users; and adding the obtained at least part of thenon-accumulated points of other users and the updated total points ofthe user together to obtain second updated total points of the user.

An eleventh feature, combinable with any of the previous or followingfeatures, further comprising: determining the updated total points ofthe user; and based on the updated total points of the user, assigning,to the user, a virtual goods corresponding to the updated total pointsof the user.

A twelfth feature, combinable with any of the previous or followingfeatures, wherein the virtual goods has different display statescorresponding to different total points.

Implementations of the subject matter and the functional operationsdescribed in this specification can be implemented in digital electroniccircuitry, in tangibly embodied computer software or firmware, incomputer hardware, including the structures disclosed in thisspecification and their structural equivalents, or in combinations ofone or more of them. Software implementations of the described subjectmatter can be implemented as one or more computer programs, that is, oneor more modules of computer program instructions encoded on a tangible,non-transitory, computer-readable computer-storage medium for executionby, or to control the operation of, data processing apparatus.Alternatively, or additionally, the program instructions can be encodedin/on an artificially generated propagated signal, for example, amachine-generated electrical, optical, or electromagnetic signal that isgenerated to encode information for transmission to suitable receiverapparatus for execution by a data processing apparatus. Thecomputer-storage medium can be a machine-readable storage device, amachine-readable storage substrate, a random or serial access memorydevice, or a combination of computer-storage mediums. Configuring one ormore computers means that the one or more computers have installedhardware, firmware, or software (or combinations of hardware, firmware,and software) so that when the software is executed by the one or morecomputers, particular computing operations are performed.

The term “real-time,” “real time,” “realtime,” “real (fast) time (RFT),”“near(ly) real-time (NRT),” “quasi real-time,” or similar terms (asunderstood by one of ordinary skill in the art), means that an actionand a response are temporally proximate such that an individualperceives the action and the response occurring substantiallysimultaneously. For example, the time difference for a response todisplay (or for an initiation of a display) of data following theindividual's action to access the data may be less than 1 ms, less than1 sec., or less than 5 secs. While the requested data need not bedisplayed (or initiated for display) instantaneously, it is displayed(or initiated for display) without any intentional delay, taking intoaccount processing limitations of a described computing system and timerequired to, for example, gather, accurately measure, analyze, process,store, or transmit the data.

The terms “data processing apparatus,” “computer,” or “electroniccomputer device” (or equivalent as understood by one of ordinary skillin the art) refer to data processing hardware and encompass all kinds ofapparatus, devices, and machines for processing data, including by wayof example, a programmable processor, a computer, or multiple processorsor computers. The apparatus can also be, or further include specialpurpose logic circuitry, for example, a central processing unit (CPU),an FPGA (field programmable gate array), or an ASIC(application-specific integrated circuit). In some implementations, thedata processing apparatus or special purpose logic circuitry (or acombination of the data processing apparatus or special purpose logiccircuitry) may be hardware- or software-based (or a combination of bothhardware- and software-based). The apparatus can optionally include codethat creates an execution environment for computer programs, forexample, code that constitutes processor firmware, a protocol stack, adatabase management system, an operating system, or a combination ofexecution environments. The present disclosure contemplates the use ofdata processing apparatuses with or without conventional operatingsystems, for example LINUX, UNIX, WINDOWS, MAC OS, ANDROID, IOS, or anyother suitable conventional operating system.

A computer program, which may also be referred to or described as aprogram, software, a software application, a module, a software module,a script, or code can be written in any form of programming language,including compiled or interpreted languages, or declarative orprocedural languages, and it can be deployed in any form, including as astand-alone program or as a module, component, subroutine, or other unitsuitable for use in a computing environment. A computer program may, butneed not, correspond to a file in a file system. A program can be storedin a portion of a file that holds other programs or data, for example,one or more scripts stored in a markup language document, in a singlefile dedicated to the program in question, or in multiple coordinatedfiles, for example, files that store one or more modules, sub-programs,or portions of code. A computer program can be deployed to be executedon one computer or on multiple computers that are located at one site ordistributed across multiple sites and interconnected by a communicationnetwork.

While portions of the programs illustrated in the various figures areshown as individual modules that implement the various features andfunctionality through various objects, methods, or other processes, theprograms may instead include a number of sub-modules, third-partyservices, components, libraries, and such, as appropriate. Conversely,the features and functionality of various components can be combinedinto single components, as appropriate. Thresholds used to makecomputational determinations can be statically, dynamically, or bothstatically and dynamically determined.

The methods, processes, or logic flows described in this specificationcan be performed by one or more programmable computers executing one ormore computer programs to perform functions by operating on input dataand generating output. The methods, processes, or logic flows can alsobe performed by, and apparatus can also be implemented as, specialpurpose logic circuitry, for example, a CPU, an FPGA, or an ASIC.

Computers suitable for the execution of a computer program can be basedon general or special purpose microprocessors, both, or any other kindof CPU. Generally, a CPU will receive instructions and data from andwrite to a memory. The essential elements of a computer are a CPU, forperforming or executing instructions, and one or more memory devices forstoring instructions and data. Generally, a computer will also include,or be operatively coupled to, receive data from or transfer data to, orboth, one or more mass storage devices for storing data, for example,magnetic, magneto-optical disks, or optical disks. However, a computerneed not have such devices. Moreover, a computer can be embedded inanother device, for example, a mobile telephone, a personal digitalassistant (PDA), a mobile audio or video player, a game console, aglobal positioning system (GPS) receiver, or a portable storage device,for example, a universal serial bus (USB) flash drive, to name just afew.

Computer-readable media (transitory or non-transitory, as appropriate)suitable for storing computer program instructions and data includes allforms of permanent/non-permanent or volatile/non-volatile memory, mediaand memory devices, including by way of example semiconductor memorydevices, for example, random access memory (RAM), read-only memory(ROM), phase change memory (PRAM), static random access memory (SRAM),dynamic random access memory (DRAM), erasable programmable read-onlymemory (EPROM), electrically erasable programmable read-only memory(EEPROM), and flash memory devices; magnetic devices, for example, tape,cartridges, cassettes, internal/removable disks; magneto-optical disks;and optical memory devices, for example, digital video disc (DVD),CD-ROM, DVD+/-R, DVD-RAM, DVD-ROM, HD-DVD, and BLURAY, and other opticalmemory technologies. The memory may store various objects or data,including caches, classes, frameworks, applications, modules, backupdata, jobs, web pages, web page templates, data structures, databasetables, repositories storing dynamic information, and any otherappropriate information including any parameters, variables, algorithms,instructions, rules, constraints, or references thereto. Additionally,the memory may include any other appropriate data, such as logs,policies, security or access data, reporting files, as well as others.The processor and the memory can be supplemented by, or incorporated in,special purpose logic circuitry.

To provide for interaction with a user, implementations of the subjectmatter described in this specification can be implemented on a computerhaving a display device, for example, a CRT (cathode ray tube), LCD(liquid crystal display), LED (Light Emitting Diode), or plasma monitor,for displaying information to the user and a keyboard and a pointingdevice, for example, a mouse, trackball, or trackpad by which the usercan provide input to the computer. Input may also be provided to thecomputer using a touchscreen, such as a tablet computer surface withpressure sensitivity, a multi-touch screen using capacitive or electricsensing, or other type of touchscreen. Other kinds of devices can beused to provide for interaction with a user as well; for example,feedback provided to the user can be any form of sensory feedback, forexample, visual feedback, auditory feedback, or tactile feedback; andinput from the user can be received in any form, including acoustic,speech, or tactile input. In addition, a computer can interact with auser by sending documents to and receiving documents from a device thatis used by the user; for example, by sending web pages to a web browseron a user's client device in response to requests received from the webbrowser.

The term “graphical user interface,” or “GUI,” may be used in thesingular or the plural to describe one or more graphical user interfacesand each of the displays of a particular graphical user interface.Therefore, a GUI may represent any graphical user interface, includingbut not limited to, a web browser, a touch screen, or a command lineinterface (CLI) that processes information and efficiently presents theinformation results to the user. In general, a GUI may include aplurality of user interface (UI) elements, some or all associated with aweb browser, such as interactive fields, pull-down lists, and buttons.These and other UI elements may be related to or represent the functionsof the web browser.

Implementations of the subject matter described in this specificationcan be implemented in a computing system that includes a back-endcomponent, for example, as a data server, or that includes a middlewarecomponent, for example, an application server, or that includes afront-end component, for example, a client computer having a graphicaluser interface or a Web browser through which a user can interact withan implementation of the subject matter described in this specification,or any combination of one or more such back-end, middleware, orfront-end components. The components of the system can be interconnectedby any form or medium of wireline or wireless digital data communication(or a combination of data communication), for example, a communicationnetwork. Examples of communication networks include a local area network(LAN), a radio access network (RAN), a metropolitan area network (MAN),a wide area network (WAN), Worldwide Interoperability for MicrowaveAccess (WIMAX), a wireless local area network (WLAN) using, for example,802.11 a/b/g/n or 802.20 (or a combination of 802.11x and 802.20 orother protocols consistent with this disclosure), all or a portion ofthe Internet, or any other communication system or systems at one ormore locations (or a combination of communication networks). The networkmay communicate with, for example, Internet Protocol (IP) packets, FrameRelay frames, Asynchronous Transfer Mode (ATM) cells, voice, video,data, or other suitable information (or a combination of communicationtypes) between network addresses.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

While this specification contains many specific implementation details,these should not be construed as limitations on the scope of anyinvention or on the scope of what may be claimed, but rather asdescriptions of features that may be specific to particularimplementations of particular inventions. Certain features that aredescribed in this specification in the context of separateimplementations can also be implemented, in combination, in a singleimplementation. Conversely, various features that are described in thecontext of a single implementation can also be implemented in multipleimplementations, separately, or in any suitable sub-combination.Moreover, although previously described features may be described asacting in certain combinations and even initially claimed as such, oneor more features from a claimed combination can, in some cases, beexcised from the combination, and the claimed combination may bedirected to a sub-combination or variation of a sub-combination.

Particular implementations of the subject matter have been described.Other implementations, alterations, and permutations of the describedimplementations are within the scope of the following claims as will beapparent to those skilled in the art. While operations are depicted inthe drawings or claims in a particular order, this should not beunderstood as requiring that such operations be performed in theparticular order shown or in sequential order, or that all illustratedoperations be performed (some operations may be considered optional), toachieve desirable results. In certain circumstances, multitasking orparallel processing (or a combination of multitasking and parallelprocessing) may be advantageous and performed as deemed appropriate.

Moreover, the separation or integration of various system modules andcomponents in the previously described implementations should not beunderstood as requiring such separation or integration in allimplementations, and it should be understood that the described programcomponents and systems can generally be integrated together in a singlesoftware product or packaged into multiple software products.

Accordingly, the previously described example implementations do notdefine or constrain this disclosure. Other changes, substitutions, andalterations are also possible without departing from the spirit andscope of this disclosure.

Furthermore, any claimed implementation is considered to be applicableto at least a computer-implemented method; a non-transitory,computer-readable medium storing computer-readable instructions toperform the computer-implemented method; and a computer systemcomprising a computer memory interoperably coupled with a hardwareprocessor configured to perform the computer-implemented method or theinstructions stored on the non-transitory, computer-readable medium.

1. (canceled)
 2. A computer-implemented method comprising: providing,for display, a first user interface that includes a control forinitiating accumulation of points that reflect an amount of carbon thatwould have been emitted by one or more carbon-emitting activities thatwere avoided through use of one or more on-line services; receiving datathat indicates a user selection of the control for initiatingaccumulation of the points; and in response to receiving the data thatindicates the user selection of the control, providing, for display, asecond user interface that includes a representation of a total numberof points that have been accumulated through the use of the one or moreon-line services.
 3. The method of claim 2, wherein the total number ofpoints that have been accumulated through the use of the one or moreon-line services comprises a particular number of points that have beenaccumulated through the use of an online payment service, and whereinthe carbon-emitting activity that was avoided through the use of theonline payment service comprises a paper consuming activity.
 4. Themethod of claim 2, wherein the total number of points that have beenaccumulated through the use of the one or more on-line servicescomprises a particular number of points that have been accumulatedthrough the use of an online ticketing service, and wherein thecarbon-emitting activity that was avoided through the use of the onlineticketing service comprises a paper consuming activity.
 5. The method ofclaim 2, wherein the total number of points that have been accumulatedthrough the use of the one or more on-line services comprises aparticular number of points that have been accumulated through the useof an online step tracking service, and wherein the carbon-emittingactivity that was avoided through the use of the online step trackingservice comprises a gasoline consuming activity.
 6. The method of claim2, wherein the total number of points that have been accumulated throughthe use of the one or more on-line services comprises a particularnumber of points that have been accumulated through the use of an onlinereservation service, and wherein the carbon-emitting activity that wasavoided through the use of the online step tracking service comprises agasoline consuming activity.
 7. The method of claim 2, wherein therepresentation comprises a virtual tree.
 8. The method of claim 2,wherein the total number of points that have been accumulated throughthe use of the one or more on-line services comprises a first particularnumber of points that have been accumulated through the use of a firstonline service and a second particular number of points that have beenaccumulated through the use of a second online service, and wherein thecarbon-emitting activity that was avoided through the use of the firstonline step tracking service comprises a first type of carbon-producingactivity, and wherein the carbon-emitting activity that was avoidedthrough the use of the second online tracking service comprises adifferent, second type of carbon-producing activity.
 9. Anon-transitory, computer-readable medium storing one or moreinstructions executable by a computer system to perform operationscomprising: providing, for display, a first user interface that includesa control for initiating accumulation of points that reflect an amountof carbon that would have been emitted by one or more carbon-emittingactivities that were avoided through use of one or more on-lineservices; receiving data that indicates a user selection of the controlfor initiating accumulation of the points; and in response to receivingthe data that indicates the user selection of the control, providing,for display, a second user interface that includes a representation of atotal number of points that have been accumulated through the use of theone or more on-line services.
 10. The medium of claim 9, wherein thetotal number of points that have been accumulated through the use of theone or more on-line services comprises a particular number of pointsthat have been accumulated through the use of an online payment service,and wherein the carbon-emitting activity that was avoided through theuse of the online payment service comprises a paper consuming activity.11. The medium of claim 9, wherein the total number of points that havebeen accumulated through the use of the one or more on-line servicescomprises a particular number of points that have been accumulatedthrough the use of an online ticketing service, and wherein thecarbon-emitting activity that was avoided through the use of the onlineticketing service comprises a paper consuming activity.
 12. The mediumof claim 9, wherein the total number of points that have beenaccumulated through the use of the one or more on-line servicescomprises a particular number of points that have been accumulatedthrough the use of an online step tracking service, and wherein thecarbon-emitting activity that was avoided through the use of the onlinestep tracking service comprises a gasoline consuming activity.
 13. Themedium of claim 9, wherein the total number of points that have beenaccumulated through the use of the one or more on-line servicescomprises a particular number of points that have been accumulatedthrough the use of an online reservation service, and wherein thecarbon-emitting activity that was avoided through the use of the onlinestep tracking service comprises a gasoline consuming activity.
 14. Themedium of claim 9, wherein the representation comprises a virtual tree.15. The medium of claim 9, wherein the total number of points that havebeen accumulated through the use of the one or more on-line servicescomprises a first particular number of points that have been accumulatedthrough the use of a first online service and a second particular numberof points that have been accumulated through the use of a second onlineservice, and wherein the carbon-emitting activity that was avoidedthrough the use of the first online step tracking service comprises afirst type of carbon-producing activity, and wherein the carbon-emittingactivity that was avoided through the use of the second online trackingservice comprises a different, second type of carbon-producing activity.16. A system comprising: one or more computers; and one or more computermemory devices interoperably coupled with the one or more computers andhaving tangible, non-transitory, machine-readable media storing one ormore instructions that, when executed by the one or more computers,perform one or more operations comprising: providing, for display, afirst user interface that includes a control for initiating accumulationof points that reflect an amount of carbon that would have been emittedby one or more carbon-emitting activities that were avoided through useof one or more on-line services; receiving data that indicates a userselection of the control for initiating accumulation of the points; andin response to receiving the data that indicates the user selection ofthe control, providing, for display, a second user interface thatincludes a representation of a total number of points that have beenaccumulated through the use of the one or more on-line services.
 17. Thesystem of claim 16, wherein the total number of points that have beenaccumulated through the use of the one or more on-line servicescomprises a particular number of points that have been accumulatedthrough the use of an online payment service, and wherein thecarbon-emitting activity that was avoided through the use of the onlinepayment service comprises a paper consuming activity.
 18. The system ofclaim 16, wherein the total number of points that have been accumulatedthrough the use of the one or more on-line services comprises aparticular number of points that have been accumulated through the useof an online ticketing service, and wherein the carbon-emitting activitythat was avoided through the use of the online ticketing servicecomprises a paper consuming activity.
 19. The system of claim 16,wherein the total number of points that have been accumulated throughthe use of the one or more on-line services comprises a particularnumber of points that have been accumulated through the use of an onlinestep tracking service, and wherein the carbon-emitting activity that wasavoided through the use of the online step tracking service comprises agasoline consuming activity.
 20. The system of claim 16, wherein thetotal number of points that have been accumulated through the use of theone or more on-line services comprises a particular number of pointsthat have been accumulated through the use of an online reservationservice, and wherein the carbon-emitting activity that was avoidedthrough the use of the online step tracking service comprises a gasolineconsuming activity.
 21. The system of claim 16, wherein therepresentation comprises a virtual tree.